FDM technology in 3D printing is a significant advancement in additive manufacturing, offering various benefits such as mass reduction, design freedom, and rapid prototyping. However, the mechanical behavior of parts depends on printing parameters. While popular and cost-effective, FDM has limitations like print time and surface finishes. Optimization of parameters, such as temperature and extrusion speed, is crucial for mechanical properties of parts. Thoughtful choices can enhance strength through density and infill pattern. Ongoing research in this field is vital for more diverse and customized applications in industries like medicine and aerospace.
Topology optimization for additive manufacturing is a rapidly evolving field that holds immense potential for revolutionizing design processes. By leveraging the capabilities of additive manufacturing, designers can explore complex geometries and intricate structures that were previously unattainable. Furthermore, the integration of additive manufacturing constraints into topology optimization methods allows for the creation of optimized designs that are not only aesthetically pleasing but also functionally superior. Additionally, this article examines the difference between the topological optimization methods most frequently and the inherent constraints of additive manufacturing that need to be which must be integrated into topological optimization formulations.
The aim of this paper is to review different methods used to evaluate additive manufacturing (AM) technologies, in particular fused deposition modeling (FDM) technique. Thus, various methods are presented. Moreover, some published scientific works related to these methods are discussed. A comparative study of these optimization methods is also carried out including their strengths and drawbacks. Despite some limitations of these methods due to FDM technology constraints, this paper shows their importance in obtaining optimal selection of 3D printing parameters.
During the last two decades, the different developments of Reliability-Based Topology Optimization (RBTO) can be divided into two groups. The first group called developments from a point of view ’topology optimization’, leading to different layouts with decreasing rigidity (increasing compliance) levels which is considered as a drawback of these methods. In addition, some researchers consider that there is no physical meaning when representing the limit state function by the prescribed volume constraint. However, the second group, being called developments from a point of view ’reliability analysis’, often leads to same layouts with increasing rigidity (or decreasing compliance) levels. The single drawback of these methods is to provide the same layouts with different thickness. Some researchers consider that this finding does not represent any importance since a detailed design stage is required to control the structural rigidity. To overcome both drawbacks, Reverse Optimum Safety Factor (ROSF) approaches are presented here to combine the two points of view to generate several layouts with increasing rigidity levels. These strategies are applied to the total hip replacement at the conceptual design stage. This way several types of hollow stems are generated considering the daily loading cases. The ROSF approaches are compared with the previous Inverse Optimum Safety Factor (IOSF) approaches. The results show that despite both approaches leading to several layouts, the ROSF approaches provide layouts with increasing rigidity (or decreasing compliance) levels. In addition to this advantage, the developed approaches lead to a decrease of material quantity in some cases (higher rigidity and less material quantity). The resulting hip stems can be additively manufactured to guarantee the configuration optimality without performing shape and sizing optimization procedures.